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If it didn’t, the outcome would either not be what was expected from the code or the computer would return an error message with no indicator of what portion of the program was written incorrectly. If the program did work, the computer would simply run the code as written. In the past, programmers would have to write an entire program and then execute it before knowing whether or not the program actually worked.
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When writing code, there is a certain trial and error method to understanding how to fix a program that just isn’t running correctly.
One of the primary ways that both students and professionals can use Jupyter Notebook is as a form of practice when writing, or learning how to write, code. This list outlines the top five uses for the Jupyter Notebook both within and outside of the classroom. Divided into front end and back end interfaces, Jupyter Notebook not only gives users access to the outcome of their code but also assists in the process of tweaking and editing the code before it is executed. Once you begin using it, it is easy to find additional information and instructions on how to use the technology and integrate it into other components that may interest you. Jupyter Notebook also gives the user access to a community of fellow users and open-source programming libraries. A tool that was made for collaboration and interactivity, Jupyter Notebook is also compatible with the most commonly used programming languages such as R, C++, Ruby, and Python. One of the best parts of using Jupyter Notebook is its flexibility and versatility, as you can work with the technology by downloading JupyterLab, or simply opening your browser to use the notebook on the go through the original application. While there are many ways to use Jupyter Notebook depending on your goals and intentions, the first step in using the notebook is getting to know the technology. Commonly used amongst educators or teams, Jupyter Notebook is especially useful for working in any type of group-setting or cloud-based environment. Within the realm of programming, notebooks act as a one-stop-shop that allows you to work on all stages of the data analysis process on one interactive page. Developed in 2014, Jupyter Notebook is an open-source collaboration technology that can be used to edit and run code using many of the most popular programming languages. Jupyter Notebook is another one of those data science tools. Whether you use programming simulators or popular exercises, there are many data science tools that make the process of learning how to code in a new programming language significantly easier.
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